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Protocol for Production of a Genetic Cross of the Rodent Malaria Parasites

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A Malaria Transmission Model with Temperature-Dependent Incubation Period.

Xiunan Wang¹, Xiao-Qiang Zhao²

¹Department of Mathematics and Statistics, Memorial University of Newfoundland, St. John's, NL, A1C 5S7, Canada. xiunan.wang@mun.ca.

Bulletin of Mathematical Biology

|April 9, 2017

Summary

This study models malaria transmission using temperature-sensitive parasite development. Results show that considering the extrinsic incubation period (EIP) is crucial for accurate malaria spread predictions, unlike using an averaged EIP.

Keywords:

Basic reproduction ratio Global attractivity Periodic delay Periodic solution Vector-borne disease

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Determining Temperature Preference of Mosquitoes and Other Ectotherms

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Published on: September 28, 2022

Area of Science:

Epidemiology
Mathematical Biology
Vector-borne Diseases

Background:

Malaria transmission is influenced by climate, affecting mosquito and parasite dynamics.
The extrinsic incubation period (EIP) of malaria parasites is temperature-dependent, impacting disease spread.
Previous models often simplify or ignore the temperature sensitivity of EIP.

Purpose of the Study:

To develop a mathematical model incorporating temperature-dependent EIP for malaria transmission.
To analyze the global dynamics of malaria spread based on the basic reproduction ratio (R0).
To assess the impact of EIP variability on malaria transmission dynamics.

Main Methods:

Formulation of a delay differential equations model with periodic time delay to represent EIP.
Derivation of the basic reproduction ratio (R0) and analysis of global dynamics.
Numerical simulations using data from Maputo Province, Mozambique.

Main Results:

A threshold dynamics result was established based on R0, determining the stability of disease-free and endemic states.
Numerical simulations confirmed the analytical findings, showing consistency between model predictions and long-term behavior.
Using a time-averaged EIP can lead to an underestimation of the basic reproduction ratio (R0).

Conclusions:

The model highlights the importance of incorporating temperature-sensitive EIP in malaria transmission dynamics.
Accurate EIP modeling is essential for reliable predictions of malaria spread and control strategies.
The study provides a more refined understanding of malaria epidemiology under varying climatic conditions.